PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

Biolab: Ingegneria Biomedica

OCT and fluorescence image standardization for GAN-based enhancement

Reference persons KRISTEN MARIKO MEIBURGER, MASSIMO SALVI

Research Groups Biolab: Ingegneria Biomedica

Description Generative adversarial networks (GANs) are a promising field of artificial intelligence for the enhancement and standardization of images from numerous modalities. Optical coherence tomography (OCT) and fluorescence microscopy are two imaging modalities that present a similarity between the acquired images: they both can tend to present objects of interest within the image that have an intensity level that is comparable to the background noise.

Thesis proposal:
The aim of the study is the implementation of semiautomatic methods for the standardization of these
images to enhance only the objects of interest while leaving the background noise untouched. The optimized images will be then used to train a GAN to generalize the semi-automatic algorithm.

See also  gans_octfluoro.pdf 


Deadline 01/04/2023      PROPONI LA TUA CANDIDATURA




© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti